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Given a Boolean function f on n variables, a Disjoint Sum-of-Products (DSOP) of f is a set of products (ANDs) of subsets of literals whose sum (OR) equals f, such that no two products cover the same minterm of f. DSOP forms are a special…

Discrete Mathematics · Computer Science 2012-04-25 Anna Bernasconi , Valentina Ciriani , Fabrizio Luccio , Linda Pagli

We present two approximate versions of the proximal subgradient method for minimizing the sum of two convex functions (not necessarily differentiable). The algorithms involve, at each iteration, inexact evaluations of the proximal operator…

Optimization and Control · Mathematics 2019-07-12 Reinier Díaz Millán , Majela Pentón Machado

This paper studies a class of simple bilevel optimization problems where we minimize a composite convex function at the upper-level subject to a composite convex lower-level problem. Existing methods either provide asymptotic guarantees for…

Optimization and Control · Mathematics 2024-03-06 Jiulin Wang , Xu Shi , Rujun Jiang

Submodular functions describe a variety of discrete problems in machine learning, signal processing, and computer vision. However, minimizing submodular functions poses a number of algorithmic challenges. Recent work introduced an…

Optimization and Control · Mathematics 2014-11-06 Robert Nishihara , Stefanie Jegelka , Michael I. Jordan

The Boolean Nearest Neighbor (BNN) representation of Boolean functions was recently introduced by Hajnal, Liu and Turan. A BNN representation of $f$ is a pair $(P,N)$ of sets of Boolean vectors (called positive and negative prototypes)…

Artificial Intelligence · Computer Science 2024-10-30 Ondřej Čepek , Jelena Glišić

We study the hardness of approximation of clause minimum and literal minimum representations of pure Horn functions in $n$ Boolean variables. We show that unless P=NP, it is not possible to approximate in polynomial time the minimum number…

Computational Complexity · Computer Science 2014-03-12 Endre Boros , Aritanan Gruber

Submodular functions are a fundamental object of study in combinatorial optimization, economics, machine learning, etc. and exhibit a rich combinatorial structure. Many subclasses of submodular functions have also been well studied and…

Data Structures and Algorithms · Computer Science 2013-04-19 Nikhil R. Devanur , Shaddin Dughmi , Roy Schwartz , Ankit Sharma , Mohit Singh

The number of quantifiers needed to express first-order (FO) properties is captured by two-player combinatorial games called multi-structural games. We analyze these games on binary strings with an ordering relation, using a technique we…

Logic in Computer Science · Computer Science 2025-08-01 Marco Carmosino , Ronald Fagin , Neil Immerman , Phokion Kolaitis , Jonathan Lenchner , Rik Sengupta

We study the approximation capabilities of two families of univariate polynomials that arise in applications of quantum signal processing. Although approximation only in the domain $[0,1]$ is physically desired, these polynomial families…

Classical Analysis and ODEs · Mathematics 2022-04-11 Rahul Sarkar , Theodore J. Yoder

We show that for the problem of minimizing (or maximizing) the ratio of two supermodular functions, no bounded approximation ratio can be achieved via polynomial number of queries, if the two supermodular functions are both monotone…

Machine Learning · Computer Science 2020-12-18 Wenxin Li

Given a collection S of subsets of some set U, and M a subset of U, the set cover problem is to find the smallest subcollection C of S such that M is a subset of the union of the sets in C. While the general problem is NP-hard to solve,…

Computational Geometry · Computer Science 2007-05-23 Kenneth L. Clarkson , Kasturi Varadarajan

In this paper we introduce two conceptual algorithms for minimising abstract convex functions. Both algorithms rely on solving a proximal-type subproblem with an abstract Bregman distance based proximal term. We prove their convergence when…

Optimization and Control · Mathematics 2026-01-09 Reinier Díaz Millán , Julien Ugon

We consider the task of locally correcting, and locally list-correcting, multivariate linear functions over the domain $\{0,1\}^n$ over arbitrary fields and more generally Abelian groups. Such functions form error-correcting codes of…

Computational Complexity · Computer Science 2024-04-29 Prashanth Amireddy , Amik Raj Behera , Manaswi Paraashar , Srikanth Srinivasan , Madhu Sudan

The minimization problem for propositional formulas is an important optimization problem in the second level of the polynomial hierarchy. In general, the problem is Sigma-2-complete under Turing reductions, but restricted versions are…

Computational Complexity · Computer Science 2011-04-13 Edith Hemaspaandra , Henning Schnoor

We investigate the strong convergence properties of a proximal-gradient inertial algorithm with two Tikhonov regularization terms in connection to the minimization problem of the sum of a convex lower semi-continuous function $f$ and a…

Optimization and Control · Mathematics 2024-07-16 Szilárd Csaba László

Approximations of non-smooth multivariate functions return low-order approximations in the vicinities of the singularities. Most prior works solve this problem for univariate functions. In this work we introduce a method for approximating…

Numerical Analysis · Mathematics 2016-10-11 Anat Amir , David Levin

A seminal result of H\r{a}stad [J. ACM, 48(4):798--859, 2001] shows that it is NP-hard to find an assignment that satisfies $\frac{1}{|G|}+\varepsilon$ fraction of the constraints of a given $k$-LIN instance over an abelian group, even if…

Computational Complexity · Computer Science 2020-09-08 Amey Bhangale , Subhash Khot

We present two novel methods for approximating minimizers of the abstract Rayleigh quotient $\Phi(u)/ \|u\|^p$. Here $\Phi$ is a strictly convex functional on a Banach space with norm $\|\cdot\|$, and $\Phi$ is assumed to be positively…

Analysis of PDEs · Mathematics 2016-02-16 Ryan Hynd , Erik Lindgren

Horn functions form a subclass of Boolean functions and appear in many different areas of computer science and mathematics as a general tool to describe implications and dependencies. Finding minimum sized representations for such functions…

Data Structures and Algorithms · Computer Science 2019-03-25 Kristóf Bérczi , Endre Boros , Ondřej Čepek , Petr Kučera , Kazuhisa Makino

We propose to approximate a (possibly discontinuous) multivariate function f (x) on a compact set by the partial minimizer arg miny p(x, y) of an appropriate polynomial p whose construction can be cast in a univariate sum of squares (SOS)…

Numerical Analysis · Mathematics 2025-07-22 Didier Henrion , Milan Korda , Jean-Bernard Lasserre
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